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Article published In:
Translation Spaces
Vol. 11:2 (2022) ► pp.184–212

Creativity in translation

Machine translation as a constraint for literary texts

ORCID logo | University of Surrey | University of Groningen
ORCID logo | University of Groningen

This article presents the results of a study involving the translation of a short story by Kurt Vonnegut from English to Catalan and Dutch using three modalities: machine-translation (MT), post-editing (PE) and translation without aid (HT). Our aim is to explore creativity, understood to involve novelty and acceptability, from a quantitative perspective. The results show that HT has the highest creativity score, followed by PE, and lastly, MT, and this is unanimous from all reviewers. A neural MT system trained on literary data does not currently have the necessary capabilities for a creative translation; it renders literal solutions to translation problems. More importantly, using MT to post-edit raw output constrains the creativity of translators, resulting in a poorer translation often not fit for publication, according to experts.

Keywords: creativity, machine translation post-editing, literary translation, creative shift, acceptability
Article outline
  • Introduction
  • Related Work
  • Research methodology
    • Source text
    • Machine translation
    • Translation process
    • Translators
    • Review process
    • Measuring creativity
      • Acceptability
      • Units of creative potential (UCP)
      • Novelty
      • Creativity scoring
    • Interviews
  • Results
    • Results on translators’ changes and effort
    • HTER
    • Translation effort according to PET
    • Results from the review
      • Post-task questionnaire
      • Acceptability
      • Creative Shifts
      • Creativity Score
    • Interviews with translators and reviewers
      • 1.MT can only be partially useful in literary translation
      • 2.Creativity is a problem-solving process
      • 3.The proposals act as a constraint to creativity
      • 4.The delicate equilibrium of reviewing
      • 5.The ideal tool for literary translation is human centred
      • 6.The technology or modality impact depends on the type of reader
      • 7.The final translation as a product of many collaborative steps
      • 8.The grim future of translation and technology
  • Conclusions
  • Acknowledgements
  • Notes
  • References
Published online: 28 March 2022
DOI logo
https://doi.org/10.1075/ts.21025.gue
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